发明名称 METHOD, SYSTEM AND COMPUTER PROGRAM PRODUCT FOR AUTOMATING EXPERTISE MANAGEMENT USING SOCIAL AND ENTERPRISE DATA
摘要 A method includes performing contextual association of entities using multi-source data. For each context the method performs co-clustering to identify distinct expert-skill associations; constructing single-entity unipartite graph representations and performing a random walk within each single-entity unipartite graph; for each single-entity unipartite graph, obtaining steady state distributions using the random walks to obtain clusters of experts and skills; performing a weighted two-way random walk across entity graphs (graph edges), giving preference to traversal within members of the same co-cluster; and performing link prediction for each context by dynamically adding edges, and obtaining overall skills predictions, analyses and inferences by merging the contexts and weighting the links of each context. The method can also use the context-specific weights obtained from the co-association information in a matrix completion procedure, and finally merge the context-specific outputs to obtain overall skills predictions, analyses and inferences. A computer program product and a system are also disclosed for performing the method.
申请公布号 US2015317376(A1) 申请公布日期 2015.11.05
申请号 US201414266970 申请日期 2014.05.01
申请人 International Business Machines Corporation 发明人 Bauer John H.;Fang Dongping;Mojsilovic Aleksandra;Ramamurthy Karthikeyan N.;Varshney Kush R.;Wang Jun
分类号 G06F17/30;G06N5/02 主分类号 G06F17/30
代理机构 代理人
主权项 1. A method implemented at least partially using a computer, comprising: performing contextual association of entities using multi-source data and for each context performing co-clustering to identify distinct expert-skill associations; constructing single-entity unipartite graph representations and performing a random walk within each single-entity unipartite graph; for each single-entity unipartite graph, obtaining steady state distributions using the random walks to obtain clusters of experts and skills; performing a weighted two-way random walk across entity graphs (graph edges), giving preference to traversal within members of the same co-cluster; and performing link prediction for each context by dynamically adding edges, and obtaining overall skills predictions, analyses and inferences by merging the contexts and weighting the links of each context.
地址 Armonk NY US